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The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem.

To the industrial engineer and many control academics this work has previously appeared fragmented; but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers. Highlights of PID Control include:

an introduction to PID control technology features and typical industrial implementations;

chapter contributions ordered by the increasing quality of the model information used;

novel PID control concepts for multivariable processes.

PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text.




The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem.

 To the industrial engineer and many control academics this work has previously appeared fragmented; but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers. Highlights of PID Control include:

an introduction to PID control technology features and typical industrial implementations;

chapter contributions ordered by the increasing quality of the model information used;

novel PID control concepts for multivariable processes.

 PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text. 




The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem.

 To the industrial engineer and many control academics this work has previously appeared fragmented; but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers. Highlights of PID Control include:

an introduction to PID control technology features and typical industrial implementations;

chapter contributions ordered by the increasing quality of the model information used;

novel PID control concepts for multivariable processes.

 PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text. 


Content:
Front Matter....Pages i-xxvii
PID Control Technology....Pages 1-46
Some PID Control Fundamentals....Pages 47-107
On-line Model-Free Methods....Pages 109-146
Automatic PID Controller Tuning — the Nonparametric Approach....Pages 147-181
Relay Experiments for Multivariable Systems....Pages 183-211
Phase-Locked Loop Methods....Pages 213-257
Phase-Locked Loop Methods and PID Control....Pages 259-296
Process Reaction Curve and Relay Methods Identification and PID Tuning....Pages 297-337
Fuzzy Logic and Genetic Algorithm Methods in PID Tuning....Pages 339-360
Tuning PID Controllers Using Subspace Identification Methods....Pages 361-388
Design of Multi-Loop and Multivariable PID Controllers....Pages 389-427
Restricted Structure Optimal Control....Pages 429-472
Predictive PID Control....Pages 473-529
Back Matter....Pages 531-543


The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem.

 To the industrial engineer and many control academics this work has previously appeared fragmented; but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers. Highlights of PID Control include:

an introduction to PID control technology features and typical industrial implementations;

chapter contributions ordered by the increasing quality of the model information used;

novel PID control concepts for multivariable processes.

 PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text. 


Content:
Front Matter....Pages i-xxvii
PID Control Technology....Pages 1-46
Some PID Control Fundamentals....Pages 47-107
On-line Model-Free Methods....Pages 109-146
Automatic PID Controller Tuning — the Nonparametric Approach....Pages 147-181
Relay Experiments for Multivariable Systems....Pages 183-211
Phase-Locked Loop Methods....Pages 213-257
Phase-Locked Loop Methods and PID Control....Pages 259-296
Process Reaction Curve and Relay Methods Identification and PID Tuning....Pages 297-337
Fuzzy Logic and Genetic Algorithm Methods in PID Tuning....Pages 339-360
Tuning PID Controllers Using Subspace Identification Methods....Pages 361-388
Design of Multi-Loop and Multivariable PID Controllers....Pages 389-427
Restricted Structure Optimal Control....Pages 429-472
Predictive PID Control....Pages 473-529
Back Matter....Pages 531-543
....
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